ArticleThe New phytologist2018
The 'PhenoBox', a flexible, automated, open-source plant phenotyping solution.
Article in The New phytologist, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed, 80 citations in OpenAlex.
- Open-source hardware platform for automated, non-invasive plant phenotyping through combined RGB and thermal imaging.HardwareX · 2026Article
- Microclimate-Controlled Smart Growth Cabinets for High-Throughput Plant Phenotyping.Sensors (Basel, Switzerland) · 2025Article
- Review
- Image analysis and polyphenol profiling unveil red-flesh apple phenotype complexity.Plant methods · 2024Article
- Article
- StripeRust-Pocket: A Mobile-Based Deep Learning Application for Efficient Disease Severity Assessment of Wheat Stripe Rust.Plant phenomics (Washington, D.C.) · 2024Article
- Development of a deep-learning phenotyping tool for analyzing image-based strawberry phenotypes.Frontiers in plant science · 2024Article
- Article
- A low-cost and open-source solution to automate imaging and analysis of cyst nematode infection assays for Arabidopsis thaliana.Plant methods · 2022Article
- Earbox, an open tool for high-throughput measurement of the spatial organization of maize ears and inference of novel traits.Plant methods · 2022Article
- A Comprehensive Review of High Throughput Phenotyping and Machine Learning for Plant Stress Phenotyping.Phenomics (Cham, Switzerland) · 2022Review
- Development of a plant conveyance system using an AGV and a self-designed plant-handling device: A case study of DIY plant phenotyping.Breeding science · 2022Article
- Opportunities and limits of controlled-environment plant phenotyping for climate response traits.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022Review
- DeepCob: precise and high-throughput analysis of maize cob geometry using deep learning with an application in genebank phenomics.Plant methods · 2021Article
- Decoding Plant-Environment Interactions That Influence Crop Agronomic Traits.Plant & cell physiology · 2020Review
- The intersection of nitrogen nutrition and water use in plants: new paths toward improved crop productivity.Journal of experimental botany · 2020Review
- Rapid identification of an Arabidopsis NLR gene as a candidate conferring susceptibility to Sclerotinia sclerotiorum using time-resolved automated phenotyping.The Plant journal : for cell and molecular biology · 2020Article
- Genebank Phenomics: A Strategic Approach to Enhance Value and Utilization of Crop Germplasm.Plants (Basel, Switzerland) · 2020Review
- Machine learning for high-throughput field phenotyping and image processing provides insight into the association of above and below-ground traits in cassava (Plant methods · 2020Article
- High-Throughput Plant Phenotyping Platform (HT3P) as a Novel Tool for Estimating Agronomic Traits From the Lab to the Field.Frontiers in bioengineering and biotechnology · 2020Review
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
There is a need for flexible and affordable plant phenotyping solutions for basic research and plant breeding. We demonstrate our open source plant imaging and processing solution ('PhenoBox'/'PhenoPipe') and provide construction plans, source code and documentation to rebuild the system. Use of the PhenoBox is exemplified by studying infection of the model grass Brachypodium distachyon by the head smut fungus Ustilago bromivora, comparing phenotypic responses of maize to infection with a solopathogenic Ustilago maydis (corn smut) strain and effector deletion strains, and studying salt stress response in Nicotiana benthamiana. In U. bromivora-infected grass, phenotypic differences between infected and uninfected plants were detectable weeks before qualitative head smut symptoms. Based on this, we could predict the infection outcome for individual plants with high accuracy. Using a PhenoPipe module for calculation of multi-dimensional distances from phenotyping data, we observe a time after infection-dependent impact of U. maydis effector deletion strains on phenotypic response in maize. The PhenoBox/PhenoPipe system is able to detect established salt stress responses in N. benthamiana. We have developed an affordable, automated, open source imaging and data processing solution that can be adapted to various phenotyping applications in plant biology and beyond.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.